Overview

Brought to you by YData

Dataset statistics

Number of variables10
Number of observations264351
Missing cells169362
Missing cells (%)6.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.0 MiB
Average record size in memory139.0 B

Variable types

Numeric8
DateTime1
Categorical1

Alerts

AFS is highly overall correlated with Bank_Type and 1 other fieldsHigh correlation
Bank_Type is highly overall correlated with AFS and 2 other fieldsHigh correlation
CET1R is highly overall correlated with T1R and 2 other fieldsHigh correlation
HTM is highly overall correlated with Bank_TypeHigh correlation
T1R is highly overall correlated with CET1R and 2 other fieldsHigh correlation
TA is highly overall correlated with AFS and 1 other fieldsHigh correlation
TCR is highly overall correlated with CET1R and 2 other fieldsHigh correlation
TLR is highly overall correlated with CET1R and 2 other fieldsHigh correlation
Bank_Type is highly imbalanced (97.7%) Imbalance
CET1R has 169362 (64.1%) missing values Missing
HTM is highly skewed (γ1 = 52.04366999) Skewed
AFS is highly skewed (γ1 = 36.93524307) Skewed
TA is highly skewed (γ1 = 38.45862545) Skewed
CET1R is highly skewed (γ1 = 88.9619804) Skewed
T1R is highly skewed (γ1 = 115.1706816) Skewed
TCR is highly skewed (γ1 = 115.1747688) Skewed
HTM has 164624 (62.3%) zeros Zeros
AFS has 20919 (7.9%) zeros Zeros

Reproduction

Analysis started2025-05-22 16:47:09.801566
Analysis finished2025-05-22 16:47:20.454276
Duration10.65 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

RSSDID
Real number (ℝ)

Distinct8278
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1052820.2
Minimum37
Maximum5336928
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 MiB
2025-05-22T12:47:20.625509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum37
5-th percentile67151
Q1333856
median664831
Q3988144
95-th percentile3429282
Maximum5336928
Range5336891
Interquartile range (IQR)654288

Descriptive statistics

Standard deviation1080080.4
Coefficient of variation (CV)1.0258926
Kurtosis0.42962024
Mean1052820.2
Median Absolute Deviation (MAD)326185
Skewness1.360476
Sum2.7831407 × 1011
Variance1.1665738 × 1012
MonotonicityIncreasing
2025-05-22T12:47:20.736351image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3821626 40
 
< 0.1%
3825080 40
 
< 0.1%
3816163 40
 
< 0.1%
3816510 40
 
< 0.1%
3804535 40
 
< 0.1%
9955 40
 
< 0.1%
10250 40
 
< 0.1%
10849 40
 
< 0.1%
11145 40
 
< 0.1%
11640 40
 
< 0.1%
Other values (8268) 263951
99.8%
ValueCountFrequency (%)
37 40
< 0.1%
242 40
< 0.1%
279 40
< 0.1%
354 40
< 0.1%
457 40
< 0.1%
505 40
< 0.1%
1155 40
< 0.1%
1351 40
< 0.1%
1454 40
< 0.1%
1557 36
< 0.1%
ValueCountFrequency (%)
5336928 1
 
< 0.1%
5303724 1
 
< 0.1%
5278251 2
 
< 0.1%
5227101 3
< 0.1%
5205819 3
< 0.1%
5193989 4
< 0.1%
5192496 4
< 0.1%
5143788 6
< 0.1%
5136959 4
< 0.1%
5086072 6
< 0.1%

HTM
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct39976
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81627.14
Minimum0
Maximum2.03157 × 108
Zeros164624
Zeros (%)62.3%
Negative0
Negative (%)0.0%
Memory size2.0 MiB
2025-05-22T12:47:20.831395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31940
95-th percentile56404.5
Maximum2.03157 × 108
Range2.03157 × 108
Interquartile range (IQR)1940

Descriptive statistics

Standard deviation1864987.3
Coefficient of variation (CV)22.847637
Kurtosis3547.5823
Mean81627.14
Median Absolute Deviation (MAD)0
Skewness52.04367
Sum2.1578216 × 1010
Variance3.4781775 × 1012
MonotonicityNot monotonic
2025-05-22T12:47:20.960878image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 164624
62.3%
500 687
 
0.3%
100 591
 
0.2%
1 459
 
0.2%
1000 393
 
0.1%
2 352
 
0.1%
200 327
 
0.1%
300 252
 
0.1%
2000 248
 
0.1%
3 237
 
0.1%
Other values (39966) 96181
36.4%
ValueCountFrequency (%)
0 164624
62.3%
1 459
 
0.2%
2 352
 
0.1%
3 237
 
0.1%
4 199
 
0.1%
5 208
 
0.1%
6 155
 
0.1%
7 149
 
0.1%
8 142
 
0.1%
9 104
 
< 0.1%
ValueCountFrequency (%)
203157000 1
< 0.1%
194472000 1
< 0.1%
163013000 1
< 0.1%
144679000 1
< 0.1%
144098000 1
< 0.1%
144023000 1
< 0.1%
142316000 1
< 0.1%
141338000 1
< 0.1%
140286000 1
< 0.1%
139228000 1
< 0.1%

AFS
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct117076
Distinct (%)44.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean373829.81
Minimum0
Maximum3.69902 × 108
Zeros20919
Zeros (%)7.9%
Negative0
Negative (%)0.0%
Memory size2.0 MiB
2025-05-22T12:47:21.062544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18307
median26573
Q371003
95-th percentile373549.5
Maximum3.69902 × 108
Range3.69902 × 108
Interquartile range (IQR)62696

Descriptive statistics

Standard deviation6770523.6
Coefficient of variation (CV)18.111246
Kurtosis1511.2571
Mean373829.81
Median Absolute Deviation (MAD)22779
Skewness36.935243
Sum9.8822283 × 1010
Variance4.5839989 × 1013
MonotonicityNot monotonic
2025-05-22T12:47:21.160590image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20919
 
7.9%
2 217
 
0.1%
1 182
 
0.1%
3 142
 
0.1%
4 107
 
< 0.1%
5 89
 
< 0.1%
6 87
 
< 0.1%
1000 78
 
< 0.1%
7 65
 
< 0.1%
500 62
 
< 0.1%
Other values (117066) 242403
91.7%
ValueCountFrequency (%)
0 20919
7.9%
1 182
 
0.1%
2 217
 
0.1%
3 142
 
0.1%
4 107
 
< 0.1%
5 89
 
< 0.1%
6 87
 
< 0.1%
7 65
 
< 0.1%
8 45
 
< 0.1%
9 26
 
< 0.1%
ValueCountFrequency (%)
369902000 1
< 0.1%
358329000 1
< 0.1%
354108000 1
< 0.1%
354075000 1
< 0.1%
353641000 1
< 0.1%
352739000 1
< 0.1%
345198000 1
< 0.1%
342757000 1
< 0.1%
335692000 1
< 0.1%
333867000 1
< 0.1%

TA
Real number (ℝ)

High correlation  Skewed 

Distinct210453
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2249182.2
Minimum0
Maximum2.21896 × 109
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.0 MiB
2025-05-22T12:47:21.272767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile28950
Q182475.5
median171337
Q3395350.5
95-th percentile2223501
Maximum2.21896 × 109
Range2.21896 × 109
Interquartile range (IQR)312875

Descriptive statistics

Standard deviation40228652
Coefficient of variation (CV)17.885902
Kurtosis1623.3871
Mean2249182.2
Median Absolute Deviation (MAD)111969
Skewness38.458625
Sum5.9457356 × 1011
Variance1.6183444 × 1015
MonotonicityNot monotonic
2025-05-22T12:47:21.378107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46035 8
 
< 0.1%
49576 8
 
< 0.1%
89639 7
 
< 0.1%
82757 7
 
< 0.1%
54411 7
 
< 0.1%
49737 7
 
< 0.1%
41382 7
 
< 0.1%
67003 7
 
< 0.1%
76209 6
 
< 0.1%
84403 6
 
< 0.1%
Other values (210443) 264281
> 99.9%
ValueCountFrequency (%)
0 2
< 0.1%
68 1
< 0.1%
91 1
< 0.1%
107 1
< 0.1%
113 1
< 0.1%
200 2
< 0.1%
207 1
< 0.1%
212 1
< 0.1%
237 1
< 0.1%
259 1
< 0.1%
ValueCountFrequency (%)
2218960000 1
< 0.1%
2198296000 1
< 0.1%
2194835000 1
< 0.1%
2167700000 1
< 0.1%
2153028000 1
< 0.1%
2152006000 1
< 0.1%
2140778000 1
< 0.1%
2138002000 1
< 0.1%
2118497000 1
< 0.1%
2096114000 1
< 0.1%

TLR
Real number (ℝ)

High correlation 

Distinct80886
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.11880714
Minimum-0.1532
Maximum5.9438
Zeros8
Zeros (%)< 0.1%
Negative125
Negative (%)< 0.1%
Memory size2.0 MiB
2025-05-22T12:47:21.489523image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-0.1532
5-th percentile0.0711
Q10.0881965
median0.100747
Q30.1197745
95-th percentile0.184879
Maximum5.9438
Range6.097
Interquartile range (IQR)0.031578

Descriptive statistics

Standard deviation0.099832454
Coefficient of variation (CV)0.84028998
Kurtosis135.93733
Mean0.11880714
Median Absolute Deviation (MAD)0.014747
Skewness8.3183095
Sum31406.788
Variance0.0099665188
MonotonicityNot monotonic
2025-05-22T12:47:21.612152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0921 303
 
0.1%
0.09 297
 
0.1%
0.0901 296
 
0.1%
0.0927 294
 
0.1%
0.0915 291
 
0.1%
0.0931 283
 
0.1%
0.0908 282
 
0.1%
0.0862 282
 
0.1%
0.0959 281
 
0.1%
0.0869 277
 
0.1%
Other values (80876) 261465
98.9%
ValueCountFrequency (%)
-0.1532 1
< 0.1%
-0.13 1
< 0.1%
-0.117925 1
< 0.1%
-0.0979 1
< 0.1%
-0.096 1
< 0.1%
-0.095522 1
< 0.1%
-0.0818 1
< 0.1%
-0.0751 1
< 0.1%
-0.0745 1
< 0.1%
-0.074259 1
< 0.1%
ValueCountFrequency (%)
5.9438 1
< 0.1%
5.1826 1
< 0.1%
3.938285 1
< 0.1%
3.0599 1
< 0.1%
2.969121 1
< 0.1%
2.789212 1
< 0.1%
2.752603 1
< 0.1%
1.843537 1
< 0.1%
1.7013 1
< 0.1%
1.619917 1
< 0.1%

CET1R
Real number (ℝ)

High correlation  Missing  Skewed 

Distinct60227
Distinct (%)63.4%
Missing169362
Missing (%)64.1%
Infinite0
Infinite (%)0.0%
Mean0.29156157
Minimum-0.124597
Maximum742.83333
Zeros1
Zeros (%)< 0.1%
Negative15
Negative (%)< 0.1%
Memory size2.0 MiB
2025-05-22T12:47:21.746957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-0.124597
5-th percentile0.103265
Q10.1249
median0.152055
Q30.198883
95-th percentile0.388747
Maximum742.83333
Range742.95793
Interquartile range (IQR)0.073983

Descriptive statistics

Standard deviation5.10083
Coefficient of variation (CV)17.494864
Kurtosis9120.3321
Mean0.29156157
Median Absolute Deviation (MAD)0.032455
Skewness88.96198
Sum27695.142
Variance26.018467
MonotonicityNot monotonic
2025-05-22T12:47:21.876804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1243 51
 
< 0.1%
0.1301 44
 
< 0.1%
0.137 40
 
< 0.1%
0.127 40
 
< 0.1%
0.1267 40
 
< 0.1%
0.1222 39
 
< 0.1%
0.1365 39
 
< 0.1%
0.1317 39
 
< 0.1%
0.1225 39
 
< 0.1%
0.1311 38
 
< 0.1%
Other values (60217) 94580
35.8%
(Missing) 169362
64.1%
ValueCountFrequency (%)
-0.124597 1
< 0.1%
-0.046745 1
< 0.1%
-0.04528 1
< 0.1%
-0.043706 1
< 0.1%
-0.043275 1
< 0.1%
-0.0408 1
< 0.1%
-0.038654 1
< 0.1%
-0.038091 1
< 0.1%
-0.0375 2
< 0.1%
-0.0348 1
< 0.1%
ValueCountFrequency (%)
742.833333 1
< 0.1%
540.82 1
< 0.1%
396.9333 2
< 0.1%
396.087591 1
< 0.1%
366.555985 1
< 0.1%
361.972973 1
< 0.1%
353.474026 1
< 0.1%
349.162338 1
< 0.1%
348.571429 1
< 0.1%
339.949686 1
< 0.1%

T1R
Real number (ℝ)

High correlation  Skewed 

Distinct106258
Distinct (%)40.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.25527404
Minimum-23
Maximum742.83333
Zeros10
Zeros (%)< 0.1%
Negative125
Negative (%)< 0.1%
Memory size2.0 MiB
2025-05-22T12:47:21.983546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-23
5-th percentile0.0976
Q10.1222
median0.148492
Q30.1938555
95-th percentile0.369304
Maximum742.83333
Range765.83333
Interquartile range (IQR)0.0716555

Descriptive statistics

Standard deviation3.4436102
Coefficient of variation (CV)13.489857
Kurtosis16519.76
Mean0.25527404
Median Absolute Deviation (MAD)0.031592
Skewness115.17068
Sum67481.948
Variance11.858451
MonotonicityNot monotonic
2025-05-22T12:47:22.088083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.125 161
 
0.1%
0.1222 159
 
0.1%
0.1153 159
 
0.1%
0.1264 155
 
0.1%
0.1313 153
 
0.1%
0.1217 153
 
0.1%
0.1267 152
 
0.1%
0.1194 152
 
0.1%
0.1346 152
 
0.1%
0.1293 150
 
0.1%
Other values (106248) 262805
99.4%
ValueCountFrequency (%)
-23 1
< 0.1%
-1.923077 1
< 0.1%
-1.2433 1
< 0.1%
-0.1896 1
< 0.1%
-0.1677 1
< 0.1%
-0.1489 1
< 0.1%
-0.146917 1
< 0.1%
-0.1434 1
< 0.1%
-0.135196 1
< 0.1%
-0.1335 1
< 0.1%
ValueCountFrequency (%)
742.833333 1
< 0.1%
540.82 1
< 0.1%
396.9333 2
< 0.1%
396.087591 1
< 0.1%
366.555985 1
< 0.1%
361.972973 1
< 0.1%
353.474026 1
< 0.1%
349.162338 1
< 0.1%
348.571429 1
< 0.1%
339.949686 1
< 0.1%

TCR
Real number (ℝ)

High correlation  Skewed 

Distinct106287
Distinct (%)40.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.26650394
Minimum-23
Maximum742.83333
Zeros9
Zeros (%)< 0.1%
Negative125
Negative (%)< 0.1%
Memory size2.0 MiB
2025-05-22T12:47:22.164245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-23
5-th percentile0.1093
Q10.133739
median0.160017
Q30.2049
95-th percentile0.379693
Maximum742.83333
Range765.83333
Interquartile range (IQR)0.071161

Descriptive statistics

Standard deviation3.4434839
Coefficient of variation (CV)12.92095
Kurtosis16520.714
Mean0.26650394
Median Absolute Deviation (MAD)0.03149
Skewness115.17477
Sum70450.582
Variance11.857582
MonotonicityNot monotonic
2025-05-22T12:47:22.255565image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1381 163
 
0.1%
0.1335 161
 
0.1%
0.1302 156
 
0.1%
0.1386 155
 
0.1%
0.1305 152
 
0.1%
0.137 150
 
0.1%
0.1427 149
 
0.1%
0.132 149
 
0.1%
0.1375 147
 
0.1%
0.1352 147
 
0.1%
Other values (106277) 262822
99.4%
ValueCountFrequency (%)
-23 1
< 0.1%
-1.923077 1
< 0.1%
-1.2433 1
< 0.1%
-0.1896 1
< 0.1%
-0.1677 1
< 0.1%
-0.1489 1
< 0.1%
-0.146917 1
< 0.1%
-0.1434 1
< 0.1%
-0.135196 1
< 0.1%
-0.1335 1
< 0.1%
ValueCountFrequency (%)
742.833333 1
< 0.1%
540.82 1
< 0.1%
396.9333 2
< 0.1%
396.087591 1
< 0.1%
366.555985 1
< 0.1%
361.972973 1
< 0.1%
353.474026 1
< 0.1%
349.162338 1
< 0.1%
348.571429 1
< 0.1%
339.949686 1
< 0.1%

Date
Date

Distinct40
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.0 MiB
Minimum2009-03-31 00:00:00
Maximum2018-12-31 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-22T12:47:22.504384image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-22T12:47:22.586564image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

Bank_Type
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.9 MiB
Small bank
263751 
Large bank
 
600

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2643510
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSmall bank
2nd rowSmall bank
3rd rowSmall bank
4th rowSmall bank
5th rowSmall bank

Common Values

ValueCountFrequency (%)
Small bank 263751
99.8%
Large bank 600
 
0.2%

Length

2025-05-22T12:47:22.664697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-22T12:47:22.724228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
bank 264351
50.0%
small 263751
49.9%
large 600
 
0.1%

Most occurring characters

ValueCountFrequency (%)
a 528702
20.0%
l 527502
20.0%
b 264351
10.0%
264351
10.0%
n 264351
10.0%
k 264351
10.0%
S 263751
10.0%
m 263751
10.0%
L 600
 
< 0.1%
r 600
 
< 0.1%
Other values (2) 1200
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2643510
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 528702
20.0%
l 527502
20.0%
b 264351
10.0%
264351
10.0%
n 264351
10.0%
k 264351
10.0%
S 263751
10.0%
m 263751
10.0%
L 600
 
< 0.1%
r 600
 
< 0.1%
Other values (2) 1200
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2643510
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 528702
20.0%
l 527502
20.0%
b 264351
10.0%
264351
10.0%
n 264351
10.0%
k 264351
10.0%
S 263751
10.0%
m 263751
10.0%
L 600
 
< 0.1%
r 600
 
< 0.1%
Other values (2) 1200
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2643510
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 528702
20.0%
l 527502
20.0%
b 264351
10.0%
264351
10.0%
n 264351
10.0%
k 264351
10.0%
S 263751
10.0%
m 263751
10.0%
L 600
 
< 0.1%
r 600
 
< 0.1%
Other values (2) 1200
 
< 0.1%

Interactions

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Correlations

2025-05-22T12:47:22.772574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
AFSBank_TypeCET1RHTMRSSDIDT1RTATCRTLR
AFS1.0000.785-0.134-0.000-0.072-0.0850.718-0.082-0.139
Bank_Type0.7851.0000.0000.5000.0510.0000.7400.0000.002
CET1R-0.1340.0001.0000.011-0.1280.996-0.3700.9930.706
HTM-0.0000.5000.0111.000-0.0950.0480.1660.0480.017
RSSDID-0.0720.051-0.128-0.0951.000-0.1060.036-0.103-0.001
T1R-0.0850.0000.9960.048-0.1061.000-0.3040.9970.743
TA0.7180.740-0.3700.1660.036-0.3041.000-0.297-0.169
TCR-0.0820.0000.9930.048-0.1030.997-0.2971.0000.742
TLR-0.1390.0020.7060.017-0.0010.743-0.1690.7421.000

Missing values

2025-05-22T12:47:19.801746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-22T12:47:20.010469image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

RSSDIDHTMAFSTATLRCET1RT1RTCRDateBank_Type
037027514868320.2021NaN0.37660.38922011-03-31Small bank
137027877835150.2033NaN0.34530.35792010-12-31Small bank
237028972824410.2059NaN0.35550.36802010-09-30Small bank
337029480818280.2018NaN0.35960.37222010-03-31Small bank
437029770836510.2004NaN0.30020.31102009-06-30Small bank
537030612833660.1988NaN0.34550.35812009-09-30Small bank
637030662821410.1995NaN0.33780.35042009-12-31Small bank
737030760848570.2056NaN0.37800.39072011-09-30Small bank
837031101815970.1988NaN0.36800.38072009-03-31Small bank
937031573845410.2008NaN0.37970.39232011-06-30Small bank
RSSDIDHTMAFSTATLRCET1RT1RTCRDateBank_Type
264341520581900455531.35262336.13001636.13001636.1300162018-06-30Small bank
264342520581907890752060.7736302.1861132.1861132.1919622018-09-30Small bank
26434352058194658117261135400.4459270.8359850.8359850.8429752018-12-31Small bank
264344522710106038568040.9082736.3105396.3105396.3140252018-06-30Small bank
26434552271010117521247280.4953861.1191871.1191871.1277542018-09-30Small bank
26434652271010146511416340.3361210.5450860.5450860.5541592018-12-31Small bank
26434752782511891941002703900220.9947197.6701897.6701897.6701892018-12-31Small bank
2643485278251191637965983890121.0088097.7310787.7310787.7310782018-09-30Small bank
2643495303724019680355051.4858002.4112642.4112642.4137412018-12-31Small bank
26435053369280025002.9691215.5555565.5555565.5555562018-12-31Small bank